Light Detection And Ranging (LiDAR) is commonly used to detect shapes of objects. A LiDAR sensor emits light pulses, which are then reflected from surfaces in surroundings of the LiDAR sensor. When reflections of the emitted light pulses return to the LiDAR sensor, corresponding signals are recorded.
Typically, the intensity of the reflected light is inversely proportional to a square of a distance between the LiDAR sensor and a surface from which the light reflected back to the LiDAR sensor.
For illustration purposes, there will now be considered an example environment in which a LiDAR sensor is implemented. In the example environment, let us consider that blocks having a height of 20 meters are placed on a planar ground surface. Let us also consider that the LiDAR sensor views the blocks from a height of 50 meters above the ground surface. Let us also consider that the blocks and the ground surface have equal reflective (and refractive) properties towards the direction of light pulses emitted by the LiDAR sensor.
A light source associated with the LiDAR sensor emits light pulses, some of which are reflected back to the LiDAR sensor from the blocks and the ground surface. The intensity of light reflected from a top surface of a given block is approximately calculated to be A/(30×30), while the intensity of light reflected from the ground surface is approximately calculated to be A/(50×50). It is evident that the intensity of the light reflected from the ground surface is merely 36% of the intensity of the light reflected from the top surface of the given block.
As an additive noise component is the same for all the signals, a Signal-to-Noise Ratio (SNR) of the signals degrades significantly when the distance between the LiDAR sensor and the surface increases. Consequently, objects that are far away from the LiDAR sensor cannot be detected easily.
One conventional method of improving an SNR involves collecting multiple measurements, and averaging the multiple measurements. The multiple measurements can be collected from a same measurement point over time. However, this requires a lot of time. Alternatively, the multiple measurements can be collected over a spatial area using multiple sensors. However, this requires collecting a large number of measurements repeatedly.